Adjusted Risk Difference Estimation: An Assessment of Convergence Problems with Application to Malaria Efficacy Studies

Mukaka, Mavuto, White, Sarah ORCID: https://orcid.org/0000-0001-5535-8075, Mwapasa, Victor, Kalilani-Phiri, Linda, Terlouw, Anja ORCID: https://orcid.org/0000-0001-5327-8995 and Faragher, Brian (2017) 'Adjusted Risk Difference Estimation: An Assessment of Convergence Problems with Application to Malaria Efficacy Studies'. Open Access Biostatistics & Bioinformatics, Vol 1, Issue 1.

Text manuscript on Risk difference estimation_Accepted version.doc - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (385kB)

Abstract

A common measure of treatment effect in malaria efficacy studies is the risk difference, which can be estimated using binomial regression models. These models can fail to provide estimates, however, due to model failure or model convergence problems. Such failure most commonly occurs when the rate is close to 0% or 100% (a “boundary problem”) but can also occur occasionally even when the rate is not close to a boundary. This paper reports the findings from simulation studies performed to evaluate the factors that may contribute to model failure when using binomial regression to derive risk difference estimates.
Convergence rates were found to fall:
i) As one or both efficacy rates moved towards a boundary value, irrespective of the number of covariates included in the model;
ii) As the numbers of covariates in the model increased;
iii) As the levels of correlation between covariates the covariates increased. In all circumstances, convergence was poor when the efficacy rate in either group was 90% or more.

Item Type:	Article
Subjects:	WC Communicable Diseases > WC 20 Research (General) WC Communicable Diseases > Tropical and Parasitic Diseases > WC 750 Malaria WC Communicable Diseases > Tropical and Parasitic Diseases > WC 755 Epidemiology
Faculty: Department:	Clinical Sciences & International Health > Clinical Sciences Department
Digital Object Identifer (DOI):	https://doi.org/10.31031/OABB.2017.01.000502
Depositing User:	Helen Wong
Date Deposited:	18 Jan 2018 11:02
Last Modified:	17 May 2022 11:09
URI:	https://archive.lstmed.ac.uk/id/eprint/8089

Statistics

View details

Actions (login required)

Edit Item